Transcript CF en macroliden

A quantitative approach to accurate
classification of RA.
Tom Huizinga
Overview of seminar
•
•
RA as a disease versus syndrome
- perspective from a disease
- perspective from a syndrome
Treatment and being quantitative
- early treatment
- treatment focussed at a target
- is there any difference in the way a target
is defined?
Classification: syndrome versus disease
•
•
•
RA=classic syndrome defined by criteria.
Now new criteria based on the decision to start
with MTX.
RA as a disorder based on pathogenesis
Syndrome
Disease
Disease subsets with
a pathway leading to
symptoms
Association between anti-CCP-responses and HLA-DRB1
SE-alleles
Leiden EAC RA patients
Controls
Anti-CCP antibodies
positive
negative
+/+
50 (25%)
16 (7%)
26 (6%)
+/-
111 (55%)
88 (41%)
153 (36%)
-/-
42 (21%)
109 (51%)
244 (58%)
SE-status*
OR allele frequency:
CCP+ vs Controls:
3.38 (2.61-4.38)
CCP- vs Controls:
1.22 (0.93-1.60)
Huizinga TW…..Criswell L, A&R, 2005
RA consists of two syndromes: ACPA+ versus ACPAACR-classification proces:
define disease based on characteristic cases
ACPA+ versus ACPA-
What about other risk factors?
Histology?
Clinical Course?
Treatment response?
RA consists of two syndromes: ACPA+ versus ACPAACR-classification proces:
define disease based on characteristic cases
HLA-SE
HLA-DR3
rs- IRF5
PTPN22
ACPA+ versus ACPArs- STAT4
rs- C5-TRAF1
rs- TNFAIP3-OLIG3
rs- CTLA4
rs- STAT4
rs- CCL21
rs-MMEL1-TNFRSF14
rs-CDK6, PRKCQ, KIF5A
CD40, IL2RA, IL2RB
Raychaudhuri S et al. Nat Genet. 2008 Oct;40(10):1216-23
van der Helm A & Huizinga T. Arthr Res Ther. 2008;10(2):205.
Huizinga et al. A&R, Arthritis Rheum. 2005 Nov;52(11):3433-8.
Conclusions
Synovitis of anti-CCP positive RA differs from antiCCP negative:
•More infiltrating lymphocytes in anti-CCP positive RA
•More fibrosis and increased synovial lining layer in anti-CCP
negative RA
•Difference is already present early in the disease
van Oosterhout M, Bajema I, Levarht EW,
Toes RE, Huizinga TW, van Laar JM.
Arthritis Rheum. 2008 Jan;58(1):53-60
Phenotype clearly different
Joint destruction over time
drug free remission rate
Fulfillment of the criteria for RA after
1 Year
2 Years
3 Years
69 CCP+ Pts
249 CCP- Pts
83%
18%
90%
24%
93%
25%
318 Pts
32%
38%
40%
#
Can the Course of UA being altered by Early
Therapy ?
Inclusion:
Primary End point:
 Undifferentiated
Arthritis
 if so verum MTX
Increase MTX based on DAS
MTX
Taper MTX to 0
15 – 30 mg
15 mg
t=0
 ACR-criteria RA
t=3
6 tabs
t=6
t=9
6 – 12 tabs
Placebo
0 mg
t = 12
t = 15
t = 18
0 tabs
30 Months Follow-up
Cumulative Survival (%)
Anti-CCP pos group (n=27)
p=0.0002
Anti-CCP neg group (n=83)
p=0.51
100
100
80
80
60
60
40
40
20
20
0
0
3
6
9
12 15 18 21 24 27 30
0
0
3
6
9
Time to diagnosis RA (months)
12 15 18 21 24 27 30
MTX group
Placebo group
Radiographic Progression
Radiographic progression
(Sharp/van der Heijde score)
Anti-CCP pos group (n=27)
p=0.03
Anti-CCP neg group (n=83)
p=0.46
49
20
15
15
10
10
5
5
0
0
0
25
50
75
100
0
25
Cumulative probability (%)
50
75
100
MTX group
Placebo group
DAS in time stratified
MTX
Placebo
ACPA pos
DAS
ACPA neg
Time (months)
Summary of ACPA positive versus ACPA negative RA
•
•
•
•
•
•
•
HLA, PTPN22, smoking point to two diseases
C5-TRAF point to two diseases
Output of WGAS studies point to two diseases
Phenotypic data more “formally” studied
Histological differences
Subanalysis of PROMPT-study
Propose as new criteria RA-type 1 and RA-type
2, to get criteria closer to pathogenesis
Overview of seminar
•
•
RA as a disease versus syndrome
- perspective from a disease
- perspective from a syndrome
Treatment and being quantitative
- early treatment
- treatment focussed at a target
- is there any difference in the way a target
is defined?
Timing and Uncertainty
General
population
Undifferentiated
arthritis
Chronic,
destructive
polyarthritis
Slowly
progressive
Rapidly
progressive
Window of Opportunity hypothesis
• Concept of time not a biological basis
• Criteria discussion leads to nosology – better to stick to probabilities
• Biology of probabilities – masterswitch
Tom Huizinga. Personal data
Lessons from Leiden Early Arthritis Cohort
Since 1993 2400
patients included with
> two year follow-up
Diagnosis at inclusion
800 undifferentiated
arthritis
40 % remission 40 % RA
900 RA
700 other
diagnosis
Prediction Rule for Development of RA
1. What is the age?
2. What is the gender?
3. How is the distribution of involved joints?
Multiply with 0.02
In case female
In case small joints hands or feet:
In case symmetric
In case upper extremities
Or:
In case upper & lower extremities
4. What is the length of the morning stiffness (minutes)?
In case 30–59 minutes
In case ≥60 minutes
5. What is the number of tender joints?
In case 4–10
In case 11 or higher
6. What is the number of swollen joints?
In case 4–10
In case 11 or more
7. What is the C-reactive protein level (mg/L)?
In case 5–50
In case 51 or higher
8. Is the rheumatoid factor positive?
If yes
9. Are the anti-CCP antibodies positive?
If yes
1 point
________
0.5 point
0.5 point
1 point
1.5 points
________
________
________
________
0.5 point
1 point
________
________
0.5 point
1 point
________
________
0.5 point
1 point
________
________
0.5 point
1.5 points
1 point
2 points
________
________
________
________
TOTAL SCORE:
van der Helm-van Mil AH, et al. Arthritis Rheum 2008;58:2241–7
________
Predicted Risk on RA vs Prediction Score
AUC
0.84
0.88
Replicated in UK, Norway,
Germany, Japan, Middle east
and Latin America
AUC=area under the curve;
van der Helm-van Mil AH, et al. Arthritis Rheum 2008;58:2241–7
Prediction Thinking is Now Implemented in the
2010 Criteria
1.
2.
3.
4.
5.
6.
7.
ACR 1987 criteria1
ACR/EULAR 2010 criteria2
Morning stiffness
Arthritis of 3 or more joint areas
Arthritis of hand joints
Symmetric arthritis
Rheumatoid nodules
Serum rheumatoid factor
Radiographic changes
1. Joint involvement
3. Acute phase reactants
– 1 medium-large joint (0)
– Normal CRP and normal
– 2–10 medium-large joints
ESR (0)
– 1–3 small joints (large joints not counted) (2)
– Abnormal CRP or
– 4–10 small joints (large joints not counted (3)
abnormal ESR (1)
– >10 joints (at least one small joint) (5)
2. Serology
4. Duration of symptoms
– Negative RF and negative ACPA (0)
– <6 weeks (0)
– Low positive RF or now positive ACPA (2)
– ≥6 weeks (1)
– High positive RF or high positive ACPA (3)
Four of these 7 criteria must be present.
Criteria 1 through 4 must have been
present for at least 6 weeks
Points are shown in parenthesis. Cut point for RA ≥6 points. Patients are also classified as
having RA if they have (a) typical erosions; (b) long-standing disease previously satisfying
the classification criteria
Early Arthritis Prediction 2007-van der Helm3
1. Age (multiply by 0.02)
2. Gender (female 1)
3. Distribution of involved joints
– Small joints hands and feet (0.5)
– Symmetric (0.5)
– Upper extremities (1)
or upper and lower extremities (1.5)
4. VAS morning stiffness
– 26–90 mm (1)
– 90 mm (2)
5. Number of tender joints
– 4–10 (0.5)
– 11 or more (1)
6. Number of swollen joints
– 4–10 (0.5)
– 11 or more (1)
7. C-reactive protein (mg/L)
– 5–50 (0.5)
– 51 or more (1.5)
8. Rheumatoid factor positive (1)
9. Anti-CCP antibodies positive (2)
Points are shown in parenthesis. Cut point for RA ≥8 points
1. Arnett FC, et al. Arthritis Rheum 1988;31:315-24; 2. New ACR/EULAR diagnostic criteria. Presented at ACR, Philadelphia, 10–16th October 2009; 3. van
der Helm-van Mil AHM, et al. Arthritis & Rheum 2007:56;433–440
A more sensitive tool for
identifying early arthritis patients
(n=2258 Leiden Early Arthritis Patients)
2010 ACR/EULAR Classification
Criteria
RA at baseline no RA at baseline
1987 ACR
Classification
Criteria
RA at baseline
644
82
no RA at baseline
455
1077
Total
1099
1159
Earlier detection of RA
297 patients fulfilled the 1987 ACR criteria during the first year,
but not at baseline
202 (68.0%) however did fulfill the 2010 criteria at baseline
RA patients classified in an earlier phase of the disease
Performance in early arthritis
Outcome Measure
MTX-initiation
Criteria Set
Sens. Spec.
AUC
DMARD-initiation
5-year Persistency
Sens. Spec. AUC
Sens. Spec. AUC
1987 ACR
Classification
Criteria
0.61
0.74
0.67
0.54
0.87
0.71
0.53
0.75
0.61
2010
ACR/EULAR
Classification
Criteria
0.84
0.60
0.72
0.74
0.74
0.74
0.71
0.65
0.65
Overview of seminar
•
•
RA as a disease versus syndrome
- perspective from a disease
- perspective from a syndrome
Treatment and being quantitative
- early treatment: biology & observational
- treatment focussed at a target
- is there any difference in the way a target
is defined?
ACPA characteristics :a biomarker of the window of
opportunity
Few isotypes
limited epitope recognition
only low avidities
Population
Many isotypes
No changes
ACPA extensive epitope
in ACPA
recognition
characteristics
high and low avidities
Undifferentiated
Artritis
Reumatoide
Artritis
The developing autoimmune response
associates with worse prognosis
Results pre-RA versus RA 2
Number of epitopes recognized by sera from:
pre-RA
RA
None
≥ 1 peptide
Recognition of
≥ 1 peptide:
Vimentin
peptide A
38%
Vimentin
peptide B
66%
Fibrinogen
peptide A
Fibrinogen
peptide B
p=0.013
Enolase
peptide
Number of epitopes recognized increase from
pre-RA to RA
Median number of peptides recognized over time
ACPA characteristics :a biomarker of the window of
opportunity
Few isotypes
limited epitope recognition
only low avidities
Population
Many isotypes
No changes
ACPA extensive epitope
in ACPA
recognition
characteristics
high and low avidities
Undifferentiated
Artritis
Reumatoide
Artritis
What is the relevance of this developing
autoimmune response during early artritis?
A broader isotype usage is associated with
Radiographic progression
EAC
* comparison ≤4 isotypes versus ≥5 isotypes: p<0.05
A broader isotype usage is associated with Radiographic
progression
EURIDISS
* comparison ≤4 isotypes versus ≥5 isotypes: p<0.05
Aim of early treatment
•
•
•
•
To prevent functional disability
To prevent structural damage
To prevent comorbidity
(cardiovascular disease, amyloidosis)
To prevent “MasterSwitches” turned on that induce
chronicity
Time
is
important
RA-only
Delay < 12 weeks
associates with:
lower rate of joint
destruction*
higher chance of
DMARD-free
remission*
Conclusion:
Delay should be
diminished
Why Recommendation 1: Window of Opportunity
General
population
Undifferentiated
arthritis
Chronic,
destructive
polyarthritis
Window of Opportunity hypothesis:
- Criteria discussion: probabilities.
- Biology of probabilities: masterswitch
- ACPA only know marker of this process
Slowly
progressive
Rapidly
progressive
Overview of seminar
•
•
RA as a disease versus syndrome
- perspective from a disease
- perspective from a syndrome
Treatment and being quantitative
- early treatment: biology & observational
- treatment focussed at a target
- is there any difference in the way a target
is defined?
Importance of patient monitoring:
evidence from RCT
• TICORA1
– Intensive: monthly, DAS guided
– Routine: every 3 months
– Remission: 65% (intensive) vs. 16% (routine)
• CAMERA2
– Intensive: monthly, computer program
– Routine: every 3 months usual care rheumatologist
– Remission: 50% (intensive) vs. 37% (routine)
1.Grigor et al. Lancet 2004; 364: 263–269
2.Verstappen et al. Ann Rheum Dis 2007; 66: 1443–1449
Importance of patient monitoring:
evidence from longitudinal patient cohorts
• Early Arthritis Cohort Leiden
– Patients treated from ’93–’95 with Pyramid strategy
– Patients treated from ’95–’98 with DMARD within
two weeks
Comparison after 4 years EAC
Survival curves of RA patients and the
general Dutch population
Delayed treatment
Survival probability
1.0
1993–1995
0.9
0.8
0.7
0.6
0
2
4
6
8
Years after inclusion
10
12
14
Early Arthritis Cohort Leiden
Survival curves of RA patients and the
general Dutch population
Early treatment
Survival probability
1.0
1996–1998
0.9
0.8
0.7
0.6
0
2
4
6
8
Years after inclusion
10
12
14
Early Arthritis Cohort Leiden
Survival curves of RA patients and the
general Dutch population
Early, aggressive treatment,
goal-driven
Survival probability
1.0
1999–2006
0.9
0.8
0.7
0.6
0
2
4
6
8
Years after inclusion
10
12
14
Early Arthritis Cohort Leiden
RA management today
• Remission
– Clinical
– Radiographic
• Low disease activity
Goals
“Remission”
Processes
“More & Better”
• Early treatment is key
• Aggressive therapy
approach with better results
• Disease activity measurement
(e.g. DAS28)
Tools
“More & Better”
• More conventional
DMARDs
• Biologics available as
highly effective
alternatives
Overview of seminar
•
•
RA as a disease versus syndrome
- perspective from a disease
- perspective from a syndrome
Treatment and being quantitative
- early treatment: biology & observational
- treatment focussed at a target
- is there any difference in the way a target
is defined?
Perspective :
?Biology?-?Swollen joint etc.?-?Function?
Biomarker-based DAS
Gene Expression
Proprietary
Molecular
Profiling
Data
1416 genes with secreted
proteins profiled in 424 RA
patients
Protein Arrays
180 proteins profiled in 410
patients
Manual
Survey of
Scientific
Publications
Literature
Review
Hundreds of
scientific articles
and posters
IRIDESCENT
Bioinformatics
Knowledge
bases
Academic database of
relationships from abstracts
Ingenuity
Commercial database of
curated scientific facts
396 Candidate Markers
Review evidence
and prioritize
Identify Assays:
Analysis of Multiple
Platforms
Optimize Assays:
Dilutions
RF Blocking
QC metrics
Shen et al. Stepwise discovery of disease activity biomarkers in rheumatoid arthritis. EULAR 2010; Poster # THU0066
42
Pre-Analytic Validity: Results Individual
Markers
Biomarker
Avg. % Difference
“OTC” vs. “Fresh”
`
-1
0.97
VEGF
121
0.85
0.97
YKL-40
80
0.87
779
0.05
COMP
1
1.00
IL6-R
0
0.56
ICAM-3
59
0.74
IL-8
83383
0.01
ICTP
-7
0.87
IL-B
2940
0.05
IL-2RA
24
0.91
Leptin
-29
0.94
IP-10
10
0.98
MDC
0
0.91
MCSF
88
0.71
MMP-1
20
0.97
OPG
32
0.23
MMP-3
-1
0.97
RANKL
0
1.00
Resistin
230
0.74
THBD
10
0.96
SAA
-4
1.00
TIMP-1
6
0.94
TNF-RI
16
0.97
Avg. % Difference
“OTC” vs. “Fresh”
R2 Conc.
[log10 pg/mL]
CRP
0
1.00
VCAM-1
EGF
1005
.58
-2
IL-6
Biomarker
ICAM-1
Qureshi et al. Pre-Analytical Effects of Serum Collection and Handling in Quantitative Immunoassays for Rheumatoid Arthritis; ACR 2010; Poster #1606
Training: Vectra™ DA Algorithm
• Includes 12 biomarkers and uses a formula similar to DAS28CRP
• Different subsets and/or weightings of biomarkers are used to estimate
SJC28, TJC28, and PG
DAS28CRP=0.56√TJC + 0.28√SJC + 0.14PG + 0.36log(CRP+1) + 0.96
TJC=tender joint count; SJC=swollen joint count; PG =patient global health
Vectra DA Score =(0.56√PTJC + 0.28√PSJC + 0.14PPG + 0.36log(CRP+1) + 0.96) * 10.53 +1
PT JC=predicted TJC, PSJC=predicted SJC, PPG =predicted PG
TJC28
Biomarkers Used To
Predict Each DAS
Component
YKL-40
SJC28
IL-6
Leptin
SAA
VEGF-A EGF
VCAM-1 TNF-RI
MMP-1
MMP-3
Resistin
Patient
Global
CRP
CRP
Bakker et al. Development of a Multi-Biomarker Test for Rheumatoid Arthritis (RA) Disease Activity (Vectra™ DA). ACR 2010; Poster #1753
Vectra™ DA Validation (RF+ and/or Anti-CCP+):
Patient Cohort Characteristics
Parameter
BRASS
Leiden
InFoRM
Total
n
87
77
66
230
Gender, % female
83
70
76
77
Median Age (IQR)
58 (48-69)
56 (45-65)
59 (50-66)
58 (48-66)
RF-positive, %
95
91
94
93
CCP-positive, %
93
87
82
88
Median Tender Joint Count (IQR)
15 (4-22)
1 (0-6)
6 (0-21)
5 (0-18)
Median Swollen Joint Count (IQR)
12 (5-17)
0 (0-4)
4 (0-11)
4 (0-12)
Median CRP in mg/L (IQR)
7 (3-15)
7 (3-17)
6 (2-21)
7 (3-17)
47 (25-70)
34 (17-50)
45 (16-70)
42 (19-65)
5.5 (3.8-6.5)
2.7 (2.0-4.2)
4.2 (2.2-6.0)
4.1 (2.3-5.8)
Mean Patient Global VAS (IQR)
Median DAS28CRP (IQR)
Curtis et al. Validation of a Multi-Biomarker Test for Rheumatoid Arthritis (RA) Disease Activity (Vectra™ DA) in a Multi-Cohort Study. ACR 2010; Poster #1782
Vectra™ DA Validation (RF+ and/or Anti-CCP+):
Results
•
•
Pearson Correlation = 0.56
The Vectra DA score was also associated with DAS28-CRP (p<0.05) within
subgroups of RA patients who were <65 years of age, ≥65, male, female,
overweight (body-mass index >25),not overweight, on anti-TNF medications, on
methotrexate but not biologics and on steroids.
Curtis et al. Validation of a Multi-Biomarker Test for Rheumatoid Arthritis (RA) Disease Activity (Vectra™ DA) in a Multi-Cohort Study. ACR 2010; Poster #1782; Data on file
Crescendo Bioscience
Vectra™ DA Validation (RF+ and/or Anti-CCP+): Ability
to Detect Low Disease Activity
•
•
The exploratory analysis shows that patients with low Vectra DA scores tended to
have a higher likelihood of low joint counts than those with low CRP
Although these results were not statistically significant, they do suggest that the
Vectra DA score may more accurately detect low joint counts than CRP.
Curtis et al. Validation of a Multi-Biomarker Test for Rheumatoid Arthritis (RA) Disease Activity (Vectra™ DA) in a Multi-Cohort Study. ACR 2010; Poster #1782
Vectra™ DA Validation (RF+ and/or Anti-CCP+):
Biomarkers Other Than CRP
• In a multivariate regression analysis of predictors of the
DAS28CRP using the Vectra DA score (without CRP) and
CRP as predictors, both the Vectra DA score (without
CRP) and CRP were statistically significant (p<0.001)
• Since the DAS28CRP includes CRP itself, a multivariate
regression analysis was carried out to evaluate both
CRP and the Vectra DA Score (without CRP) as
predictors of the DAS28CRP with CRP removed
– The Vectra DA score (without CRP) was statistically
significant (p<0.001), and the CRP term was not significant
(p=0.22).
Curtis et al. Validation of a Multi-Biomarker Test for Rheumatoid Arthritis (RA) Disease Activity (Vectra™ DA) in a Multi-Cohort Study. ACR 2010; Poster #1782
BeSt
Treatment Strategies
in Rheumatoid Arthritis
Predictors of HAQ response after 3
months of treatment with different
strategies in recent onset active RA are
different than predictors of rapid
radiological progression
BeSt trial
Sequential
monotherapy
n=126
MTX
monotherapy
Step-up
combination
n=121
MTX
monotherapy
Initial combination
with prednisone
n=133
Initial combination
with infliximab
n=128
MTX + SSA + pred
MTX + IFX
Each strategy further treatment steps per 3 months
if DAS >2.4
Predictors RRP
Predictors
Odds ratio
95% CI
RF/ACPA both negative
1 positive
both positive
ref
2.5
4.0
1.01-6.1
1.9-8.5
Erosions
ref
1.3
3.8
0.6-3.1
1.6-8.9
0
1-4
4
CRP mg/L <10
10-35
35
Therapy
mono
combi prednisone
combi IFX
ref
1.5
4.8
ref
0.2
0.1
0.7-3.2
2.3-9.7
0.1-0.4
0.1-0.3
Matrix: RRP after 1 year of treatment
Initial monotherapy
10-35
<10
47
47
24
24
19
19
22
22
9
9
7
7
16
16
6
6
5
5
-/-
69
69
44
44
37
37
42
42
20
20
16
16
32
32
14
14
11
11
78
78
56
56
49
49
54
54
29
29
23
23
43
43
21
21
17
17
4
1-4
0
4
1-4
0
4
1-4
0
Risk of RRP (%)
Erosions (number)
CRP (mg/L)
35
<10
10-20
20-50
50
+/- or -/+
+/+
RF and ACPA
Initial combination with prednisone
42
42
20
20
16
16
19
19
8
8
6
6
13
13
5
5
4
4
+/+
4
1-4
0
4
1-4
0
4
1-4
0
35
CRP (mg/L)
<10
30
30
13
13
10
10
12
12
5
5
4
4
8
8
3
3
2
2
+/- or -/+
RF and ACPA
10-35
<10
11
11
44
3
3
4
4
1
1
1
1
3
3
1
1
1
1
-/-
24
24
10
10
8
8
9
9
3
3
3
3
6
6
2
2
2
2
+/- or -/+
RF and ACPA
34
34
15
15
12
12
14
14
6
6
4
4
10
10
3
3
3
3
+/+
4
1-4
0
4
1-4
0
4
1-4
0
Erosions (number)
10-35
15
15
66
4
4
5
5
2
2
1
1
4
4
1
1
1
1
-/-
Erosions (number)
CRP (mg/L)
35
Initial combination with IFX
Predictors HAQ >=1
Baseline predictors
OR (95% CI)
Initial treatment
mono
combo prednisone
combo infliximab
ref
0.3 (0.2 - 0.5)
0.4 (0.2 - 0.6)
HAQ
< 1.4
1.4 - 2.0
> 2.0
ref
2.6 (1.6 - 4.2)
5.3 (2.9 - 9.5)
VAS pain
(tertiles)
< 40
40 - 60
> 60
ref
2.2 (1.3 - 3.8)
2.7 (1.4 - 5.1)
RAI
(tertiles)
< 10
10 -16
> 16
ref
1.7 (1.02 - 3.0)
2.7 (1.5 - 4.7)
Matrix: predicted risk HAQ ≥ 1 after 3 months
Monotherapy
1.4 - 2
< 1.4
73
86
88
>16
64
80
83
10-16
51
70
74
<10
58
75
79
>16
47
66
70
10-16
34
53
58
<10
34
53
58
>16
25
43
48
10-16
16
30
35
<10
< 40
40-60
>60
High risk
Intermediate risk
RAI
HAQ
>2
Lower risk
Low risk
VAS pain
Combo with prednisone
1.4 - 2
<1.4
45
64
69
50
68
73
>16
35
54
59
39
58
63
10-16
23
40
45
27
45
50
<10
29
47
52
25
46
51
>16
21
37
41
24
41
46
10-16
13
25
29
15
29
33
<10
14
25
29
16
29
33
>16
9
18
21
11
21
25
10-16
5
11
14
7
13
16
<10
< 40
40-60
>60
< 40
40-60
>60
VAS pain
RAI
HAQ
>2
Combo with infliximab
Differences RRP and HAQ model
• Of all 508 patients in the BeSt, 12% had a HAQ
≥ 1 after three months of treatment as well as
RRP after one year.
• Thus, it seems that short-term functional ability
and radiological damage progression are
different concepts.
• The choice of the best initial treatment is
dependent on the relevance of the respective
outcome measures for an individual patient.
Which target is relevant for which patient?
Relevance of CCP-test
Patient develops
symptoms
GP refers patient to
Rheumatologist
Patient visits GP
DELAY has a price (less
remission, more destruction,
more suffering)
Guidance of treatment
possible by prediction
based on serum-based
Measure disease activity measurments or
activity
measurements focussed
at prevention of damage
versus function